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Targeted DNA Methylation Analysis by Next-generation Sequencing
Published on: February 24, 2015
Linkage disequilibrium based genotype calling from low-coverage shotgun sequencing reads
Jorge Duitama1, Justin Kennedy, Sanjiv Dinakar
1Department of Computer Science & Engineering, University of Connecticut, 371 Fairfield Rd, Unit 2155, Storrs, CT 06269-2155, USA. jduitama@engr.uconn.edu
BMC Bioinformatics
|February 24, 2011
Summary
Integrating linkage disequilibrium (LD) information with low-coverage sequencing data significantly improves genotype calling accuracy. This makes low-coverage sequencing a cost-effective alternative to microarrays for large-scale genetic studies.
Area of Science:
- Genomics
- Bioinformatics
- Population Genetics
Background:
- Advances in genome sequencing offer revolutionary potential for biomedical research.
- Whole-genome SNP genotyping using deep sequencing is currently more expensive than microarray technology.
Purpose of the Study:
- To develop a novel statistical model and efficient algorithms for genotype calling.
- To integrate shotgun sequencing data with linkage disequilibrium (LD) information for improved accuracy.
Main Methods:
- Introduction of a multi-locus statistical model.
- Development of computationally efficient genotype calling algorithms.
- Integration of LD information from reference panels (e.g., Hapmap, 1000 Genomes).
Main Results:
- Genotype calling accuracy comparable to microarrays achieved with low-coverage sequencing data.
- Demonstrated effectiveness across diverse sequencing platforms (454, Illumina, ABI SOLiD).
- A software package (GeneSeq) is available under GNU GPL.
Conclusions:
- Integrating LD information substantially enhances genotype calling accuracy over LD-oblivious methods.
- Low-coverage sequencing emerges as a feasible alternative to microarrays for genome-wide association studies.
- Enables cost-effective large-scale genetic research.